Book Image

Azure Data Engineer Associate Certification Guide

By : Newton Alex
Book Image

Azure Data Engineer Associate Certification Guide

By: Newton Alex

Overview of this book

Azure is one of the leading cloud providers in the world, providing numerous services for data hosting and data processing. Most of the companies today are either cloud-native or are migrating to the cloud much faster than ever. This has led to an explosion of data engineering jobs, with aspiring and experienced data engineers trying to outshine each other. Gaining the DP-203: Azure Data Engineer Associate certification is a sure-fire way of showing future employers that you have what it takes to become an Azure Data Engineer. This book will help you prepare for the DP-203 examination in a structured way, covering all the topics specified in the syllabus with detailed explanations and exam tips. The book starts by covering the fundamentals of Azure, and then takes the example of a hypothetical company and walks you through the various stages of building data engineering solutions. Throughout the chapters, you'll learn about the various Azure components involved in building the data systems and will explore them using a wide range of real-world use cases. Finally, you’ll work on sample questions and answers to familiarize yourself with the pattern of the exam. By the end of this Azure book, you'll have gained the confidence you need to pass the DP-203 exam with ease and land your dream job in data engineering.
Table of Contents (23 chapters)
1
Part 1: Azure Basics
3
Part 2: Data Storage
10
Part 3: Design and Develop Data Processing (25-30%)
15
Part 4: Design and Implement Data Security (10-15%)
17
Part 5: Monitor and Optimize Data Storage and Data Processing (10-15%)
20
Part 6: Practice Exercises

Optimizing pipelines for analytical or transactional purposes

You have surely heard the terms OLAP and OLTP if you have been working in the data domain. Cloud data systems can be broadly classified as either Online Transaction Processing (OLTP) or Online Analytical Processing (OLAP) systems. Let's understand each of these at a high level.

OLTP systems

OLTP systems, as the name suggests, are built to efficiently process, store, and query transactions. They usually have transaction data flowing into a central ACID-compliant database. The databases contain normalized data that adheres to strict schemas. The data sizes are usually smaller, in the range of gigabytes or terabytes. Predominantly RDBMS-based systems, such as Azure SQL and MySQL, are used for the main database.

OLAP systems

On the other hand, OLAP systems are usually big data systems that typically have a warehouse or key value-based store as the central technology to perform analytical processing. The tasks...